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Titlebook: Advances in Information Retrieval; 31th European Confer Mohand Boughanem,Catherine Berrut,Chantal Soule-Du Conference proceedings 2009 Spri

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楼主: Heel-Spur
发表于 2025-3-23 10:29:53 | 显示全部楼层
Sadhan Kumar Ghosh,Sannidhya Kumar Ghoshunderstanding of blog search has deepened considerably. But there’s more to user generated content than blogs and there’s more to searching user generated content than looking for material that is relevant or opinionated or highly rated by readers or authors. In this talk, a number of user generated
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Antonella Zucchella,Sabine UrbanP) suggests that, for optimal retrieval, documents should be ranked in order of decreasing probability of relevance. In this paper, we present a new document ranking paradigm, arguing that a better, more general solution is to optimize top-. ranked documents as a whole, rather than ranking them inde
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https://doi.org/10.1007/978-3-030-52689-4be integrated into the retrieval process. We evaluate the effectiveness of different types of topic models within those retrieval approaches. We show that: (1) topic models are effective for document smoothing; (2) more rigorous topic models such as Latent Dirichlet Allocation provide gains over clu
发表于 2025-3-24 02:41:59 | 显示全部楼层
Mei-Sheng Xiao,Jeremy E. Wilusza shared information need. To date most SCIR systems have focussed on providing various awareness tools in order to enable collaborating users to coordinate the search task. However, requiring users to both search and coordinate the group activity may prove too demanding. On the other hand without e
发表于 2025-3-24 07:25:28 | 显示全部楼层
Suman Singh,Aniruddha Das,Amaresh C. Pandaent state-of-the-art systems fail to consider the underlying semantics involved when rating an item. This in turn contributes to many false recommendations. These models hinder the possibility of explaining . or .. In this paper, we develop an approach incorporating the underlying semantics involved
发表于 2025-3-24 10:42:45 | 显示全部楼层
Xu-Kai Ma,Xiang Gao,Mei Cao,Li Yang eight search strategies that divided labour and shared knowledge in teams using relevance feedback and clustering. We evaluated the performance of strategies with a user simulation enhanced by a query-pooling method. Our results show that relevance feedback is successful at formulating effective co
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https://doi.org/10.1007/978-1-0716-3678-7on past queries is used to estimate term weights for new queries. This generalization is achieved by introducing secondary features correlated with term weights and applying regression to predict term weights given features. To improve support for more focused retrieval like question answering, we c
发表于 2025-3-25 02:32:46 | 显示全部楼层
Directed Circularization of a Short RNAunlabeled examples in terms of how much further information they would carry, once manually labeled, for retraining a (hopefully) better classifier. Research on active learning in text classification has so far concentrated on single-label classification; active learning for multi-label classificati
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